Spatial pattern of congenital toxoplasmosis incidence and its relationship with vulnerability and national health indicators in Brazil.

There is a gap in evidence regarding spatial clusters of the congenital toxoplasmosis (CT) and its association with social and health indicators in the Brazilian territory. Thus, we aimed herein to identify CT risk areas in Brazil and its association with social vulnerability and health indicators. An ecological and population-based study was conducted.

Spatial analysis of hospital-related mortality due to COVID-19 among children and adolescents in Brazil.

The objective was to perform a spatial analysis of the hospital mortality rate (HMR) due to severe acute respiratory syndrome (SARS) attributed to COVID-19 among children and adolescents in Brazil from 2020 to 2021. A cluster method was used to group federal units (FUs) based on HMR. In 2020, clusters with high HMRs were formed by north/northeast FUs.

Spatio-temporal analysis of leptospirosis in Brazil and its relationship with flooding.

Leptospirosis is a serious public health problem in Brazil, which can be observed after flooding events. Using an exploratory mixed clustering method, this ecological study analyzes whether spatial-temporal clustering patterns of leptospirosis occur in Brazil. Data from the Brazilian Unified Health System (SUS) were used to calculate the prevalence of leptospirosis between 2007 and 2017 in all counties of the country.

[Tuberculosis and diabetes comorbidity in Brazil, 2012-2018: exploratory spatial data analysis and statistical modelingLa comorbilidad tuberculosis-diabetes en Brasil, 2012-2018: análisis exploratorio de la distribución espacial y modelización estadística].

Objective: To describe the spatial distribution of tuberculosis-diabetes comorbidity and identify the social determinants of the double burden of disease in the period from 2012 to 2018 in Brazil.

Method: In the present ecological study, municipalities were the unit of analysis. All cases of tuberculosis reported from 2012 to 2018 to the National Notifiable Disease Information System SINAN were included.

Autoregressive spatial modeling of possible cases of dengue, chikungunya, and Zika in the capital of Northeastern Brazil.

Introduction: Dengue, chikungunya, and Zika are a growing global health problem. This study analyzed the spatial distribution of dengue, chikungunya, and Zika cases in São Luís, Maranhão, from 2015 to 2016 and investigated the association between socio-environmental and economic factors and hotspots for mosquito proliferation.

Methods: This was a socio-ecological study using data from the National Information System of Notifiable Diseases.

Spatial analysis of probable cases of dengue fever, chikungunya fever and zika virus infections in Maranhao State, Brazil.

Dengue fever, chikungunya fever, and zika virus infections are increasing public health problems in the world, the last two diseases having recently emerged in Brazil. This ecological study employed spatial analysis of probable cases of dengue fever, chikungunya fever, and zika virus infections reported to the National Mandatory Reporting System (SINAN) in Maranhao State from 2015 to 2016. The software GeoDa version 1.